CVE-2026-84372 (GCVE-0-2026-84372)
Vulnerability from cvelistv5 – Published: 2026-09-01 21:20 – Updated: 2026-09-02 19:33
VLAI
EPSS
VEX
Title
Predis: Redis command injection and denial of service via CRLF smuggling in pipelined commands on aggregate connections
Summary
Predis is a flexible and feature-complete Redis and Valkey client for PHP. From version 3.0.0-RC1 until version 3.3.0, pipeline handling on aggregate cluster and replication connections reparses an already serialized RESP buffer in AbstractAggregateConnection::write() by splitting it with explode("\r\n") instead of honoring RESP length prefixes. Attacker-controlled keys or values containing CRLF sequences can therefore be interpreted by Command::deserializeCommand() as additional commands. On cluster connections, ClusterStrategy::getFakeKey() can route injected keyless commands using the literal fake key value "key", permitting operations such as shard-wide cache deletion, targeted data modification, data reads, or node disruption. On replication connections, malformed reparsing can throw an uncaught exception and repeatedly terminate affected requests. Only pipeline() reaches this vulnerable path; transaction() and MULTI are not affected. This issue is fixed in version 3.3.0.
Severity
9.8 (Critical)
SSVC
Exploitation: poc
Automatable: yes
Technical Impact: total
CISA Coordinator · CISA-ADP (v2.0.3)
Decision recorded 2026-09-02 19:16 UTC
CWE
- CWE-93 - Improper Neutralization of CRLF Sequences ('CRLF Injection')
Assigner
References
5 references
| URL | Tags |
|---|---|
| https://github.com/predis/predis/security/advisor… | x_refsource_CONFIRM |
| https://github.com/predis/predis/issues/1574 | x_refsource_MISC |
| https://github.com/predis/predis/pull/1586 | x_refsource_MISC |
| https://github.com/predis/predis/commit/053cb4b6a… | x_refsource_MISC |
| https://github.com/predis/predis/releases/tag/v3.3.0 | x_refsource_MISC |
Impacted products
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Experimental. This forecast is provided for visualization only and may change without notice. Do not use it for operational decisions.
Forecast uses a logistic model when the trend is rising, or an exponential decay model when the trend is falling. Fitted via linearized least squares.
Sightings
| Author | Source | Type | Date | Other |
|---|
Nomenclature
- Seen: The vulnerability was mentioned, discussed, or observed by the user.
- Confirmed: The vulnerability has been validated from an analyst's perspective.
- Published Proof of Concept: A public proof of concept is available for this vulnerability.
- Exploited: The vulnerability was observed as exploited by the user who reported the sighting.
- Patched: The vulnerability was observed as successfully patched by the user who reported the sighting.
- Not exploited: The vulnerability was not observed as exploited by the user who reported the sighting.
- Not confirmed: The user expressed doubt about the validity of the vulnerability.
- Not patched: The vulnerability was not observed as successfully patched by the user who reported the sighting.
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The MITRE ATT&CK techniques below are AI-generated suggestions, inferred from the description of the
vulnerability by the CIRCL/vulnerability-attack-technique-classification-roberta-base
model, served locally by ML-Gateway.
They have not been verified by an analyst and are provided for guidance only.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
The approach is described in our paper Mapping CVEs to MITRE ATT&CK Techniques: A Curated Gold-Set Classifier and the Limits of LLM-Assisted Label Expansion.
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